We propose an iterative procedure to efficiently estimate models with complex log-likelihood functions and the number of parameters relative to the observations being potentially high. Given consistent but inefficient estimates of sub-vectors of the parameter vector, the procedure yields...

Operationalizing the capability approach (CA) is difficult due to the conceptual challenges it poses: its multidimensionality and the role it assigns to freedom of choice for human wellbeing. Therefore the operationalizability of the CA has been questioned. Despite this, a lot of empirical...

This paper uses the method developed by Bollerslev and Todorov (2011b) to estimate risk premia for extreme events for the US and the German stock markets. The method extracts jump tail measures from high-frequency futures price data and from options data. In a second step, jump tail...

In this paper we explore the application of Generalised Additive Models of Location, Scale and Shape for the analysis of conditional income distributions in Germany following the reunification. We find that conditional income distributions can generally be modelled using the three parameter...

A measurement error model is a regression model with (substantial) measurement errors in the variables. Disregarding these measurement errors in estimating the regression parameters results in asymptotically biased estimators. Several methods have been proposed to eliminate, or at least to...

The method for estimation and testing for cointegration put forward by Johansen assumes that the data are described by a vector autoregressive process. In this article we extend the data generating process to autoregressive moving average models without unit roots in the MA polynomial. We first...

This paper examines the consequences of using self-reported measures of BMI when estimating the effect of BMI on income for women using both Irish and US data. We find that self-reported BMI is subject to substantial measurement error and that this error deviates from classical measurement...

Complex phenomena in environmental sciences can be conveniently represented by several inter-dependent random variables. In order to describe such situations, copula-based models have been studied during the last year. In this paper, we consider a novel family of bivariate copulas, called...

This paper studies the decision made by a family to invest in student migration. We propose an empirical structural decision model which reflects the importance of both the return to the investment and the budgetary constraint in the choice of the family. We circumvent the problem of endogeneity...

This paper presents a New Keynesian DSGE model with inventory holding firms. The model distinguishes between goods and materials, for both production as well as for inventories. The more detailed treatment of inventory holdings offers new insights into the determinants of business cycles before...